GA-based Parameter Optimization of Image Processing for Contamination Inspection of Nonwoven Fabrics

The paper proposes the parameter optimization of image processing for contamination inspection of nonwoven fabrics. Currently, the automation of contamination inspection using image processing systems is being considered. In image processing, it is important to set the optimal parameters for the processing. However, it is necessary to search it from many combinations because there are some parameters. The proposed method searches for the optimal parameters based on a genetic algorithm. It reduces the search time in comparison with the conventional method. The paper indicates the effectiveness of the proposed method with the experimental results.